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Although decision trees are frequently used in environmental decision support systems they have shortcomings. In case of an available model decision trees have to be constructed manually from the model. Moreover, not all knowledge is represented in the decision tree. In order to overcome this issues we propose the use of abductive reasoning directly applied to the available cause-effect model. In particular we introduce the abduction problem, i.e., the problem of finding a cause for observed effects, show how this problem can be extended in order to allow distinguishing between competing explanations, and discuss the integration of testing and repair actions within the framework. The latter is especially important in case of environmental decision support systems.